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IDE coding assistant for VS Code and JetBrains that uses your own API keys across 15+ model providers, with agentic mode and autocomplete.
Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.
Open-source terminal AI pair programmer that edits code in your local git repo and auto-commits, working with most LLMs.
Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
AI-powered code editor with agentic workflows for developers.
No public pricing
No public pricing
No public pricing
- ✦BYOK access to 15+ model providers
- ✦Agentic planning-then-build mode
- ✦AI autocomplete
- ✦MCP connections to external systems
- ✦Custom rules and live context tracking
- ✦Local models via Ollama/LM Studio
- ✦VS Code and JetBrains plugins
- ✦Codebase-aware developer chat
- ✦AI code completions and inline edits
- ✦Customizable and shareable prompts
- ✦Automatic bug identification and debugging help
- ✦Context filters to exclude sensitive repos
- ✦Integrates with major code hosts and IDEs
- ✦Terminal-based AI pair programming
- ✦Edits code in your local git repo
- ✦Automatic git commits with messages
- ✦Codebase mapping for large projects
- ✦Works with cloud and local LLMs
- ✦Voice-to-code, image/web context, lint and test
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦AI-powered code completion and suggestions
- ✦Automated lint fixing
- ✦Cascade agent for advanced coding assistance
- ✦Integrated app building and deployment
- ✦MCP server support for custom tools
- ✦Terminal command integration
- ✦Memory of codebase structure and workflow
- →Code generation, refactoring and debugging
- →Control AI spend with your own keys
- →Switch between frontier models per task
- →Keep code private and data-sovereign
- →Engineers asking questions about an unfamiliar large codebase
- →Teams standardizing common coding tasks with shared prompts
- →Developers debugging errors faster with AI-assisted context
- →Enterprises running large-scale code migrations
- →Building features and fixing bugs via AI in the terminal
- →Working on large existing codebases
- →Automating git commits
- →Using local LLMs for private coding
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Accelerating software development by automating repetitive tasks
- →Reducing onboarding time for new developers
- →Improving code quality and reducing tech debt
- →Streamlining the app building and deployment process
- →Enhancing developer productivity by keeping them in a state of flow